Some Of These Tickets Can't Be Real

Content Programming in high school and college: I can write a function to check if a number is a palindrome, a "Dog" class that overrides methods of the "Animal" class, and a dictionary that receives the real name of a superhero as key and returns their secret identity. I suppose that I have enough practice to start the next unicorn that will disrupt a major tech industry. imgtip FIVE YEARS LATER, SEARCHING FOR WORK: hi "What are all of these arcane symbols? How do I unit test? Who is JSON, and why is the letter 'A' missing in his name?" imgfli ProgrammerHumor. io

That suspicious QA Manager face is the universal constant of software development. Code passing all tests without a single bug is like finding a unicorn—mythical and slightly terrifying. The cat's skeptical glare perfectly captures that moment when your QA Manager is silently calculating how many bugs are actually hiding in your "flawless" code. They've seen too many production disasters that started with "it worked on my machine" to believe your zero-bug fairy tale. They're lurking around corners, peeking through doors, and plotting more edge cases that'll make your code crumble faster than a house of cards in a hurricane.

When your bug becomes a "feature" and you have to pretend it was intentional all along. The Dale Gribble approach to software development – just blame it on a conspiracy and claim it's working exactly as designed. That moment when QA asks why the login button teleports users to Narnia, and you're like "That's not a bug, that's our new dimensional travel feature. We're disrupting the space-time continuum market."

The perfect representation of code review culture in the wild. Guy 1 frantically points out someone's terrible code like it's a five-alarm fire, while Guy 2 delivers the crushing reality check: absolutely nobody gives a damn. The same devs who'll argue for hours about tabs vs. spaces will happily ignore a production codebase that looks like it was written by randomly mashing a keyboard. Welcome to software engineering, where we're simultaneously perfectionists and completely fine with duct-taped solutions that "just work." The duality of programmer.

Oh. My. GOD. The absolute TRAGEDY of modern development! 😭 You start with ONE measly problem that's driving you insane. Then your sleep-deprived brain thinks, "ChatGPT will save me!" But PLOT TWIST! Now you're drowning in a sea of strawberry-themed errors because ChatGPT decided to hallucinate an entire fruit salad of solutions! Is it "strawberry" or "strawbery" or "strawberrrrrry"?! WHO KNOWS ANYMORE?! The AI doesn't! And now instead of fixing one problem, you're questioning your entire career choice while debugging AI-generated code that's about as reliable as a chocolate teapot. The circle of developer suffering is COMPLETE!

Content README.md FauxPilot This is an attempt to build a locally hosted version of GitHub Copilot. It uses the SalesForce CodeGen models inside of NVIDIA's Triton Inference Server with the FasterTransformer backend. Prerequisites You'll need: Docker docker -compose 1.28 An NVIDIA GPU with enough VRAM to run the model you want. nvidia-docker Note that the VRAM requirements listed by setup. sh are total - if you have multiple GPUs, you can split the model across them. So, if you have two NVIDIA RTX 3080 GPUs, you should be able to run the 6B model by putting half on each GPU Support and Warranty Imao